As far back as 3,500 years ago, Egyptian doctors were performing invasive surgeries. Even though our tools and knowledge have improved since then, until very recently surgery was still a manual task for human hands.
About 15 years ago, Intuitive Surgical's da Vinci surgical robot was a new surgery device, that is routinely used to help surgeons be more precise, especially to remove natural hand tremors during surgery.
Since Intuitive Surgical's da Vinci surgical robot arrival, there have been many other surgical robots introduced. Today we are in a new wave of innovation that is best characterized by the convergence of surgical robotics with artificial intelligence (AI) and data gathered from robotic systems. We are now “digitizing” surgery by collecting and analyzing data passing through these robotic systems, such as in-motion tracking, capturing images, etc. This then allows for enhancements to the surgical processes.
For example, minimally invasive spine surgery has recently been advanced with the use of endoscopes, with innovations in the imaging equipment and advances in medical robotics. Advantages thankfully are to the patient with less pain, smaller incisions, fewer complications and rapid return to normal activity as compared to conventional surgery. Surgeons are now able to remove a ruptured disc with a very small endoscope and repair a painful disc with the aid of a miniature camera and incisions no larger than 0.5 inch. Robotics and computers are now playing an expanding role in assisting the surgeon in these minimally invasive procedures where the surgeon sits at a station peering at a monitor that shows a magnified view of the surgical field. A computer mimics and enhances the surgeon's hand movements. The computer in this instance makes the movements more precise by dampening even a tiny tremor in the surgeon's hands, which might increase the difficulty in performing procedures under high power microscopic magnification. Even with the robot enhancing the surgeon's ability, a great deal of practice is required to master the technique.
Robots are also used to help in performing tasks that may be fatiguing for surgeons. This idea formed “AESOP” which is a natural language voice-activated robotic arm that holds the camera and endoscope assembly for the surgeon during an endoscopic procedure. This innovation reduces the need for a person to be required to do this task and improves the result by moving precisely where the surgeon commands the robot, providing a steady image.
Computers are also being used in image guidance systems to give the surgeon real-time images and allow him to navigate to the specific location on the spine. The surgeon can use digital information obtained before surgery such as MRI or CAT scans or use real-time fluoroscopic x-rays to develop a three-dimensional image of the spine with the exact location of a probe placed on the spine. This technology has been shown to minimize errors in placement of pedicle screws that are sometimes used to fix the spine. It is also expected that this technology will expand to allow more precise targeting of the problem with minimal incisions and fewer surgical complications.
The use of robotics and computers in minimally invasive spine surgery has resulted in more accurate surgical procedures, shortened operative time and fewer complications. It is expected that Computer-Enhanced Image Guidance Systems will improve the precision of these procedures because of real-time 3-D imaging at the time of the surgery. Diagnostic studies will be digitally transmitted to the operating room and projected to monitors to further aid the surgeon in performing the correct procedure with minimal trauma to the patient.
Today there are basically three types of AI used for surgery. The first is by IBM in its Watson System, which uses an expert-system type of AI. Watson stores vast medical information and gives responses to natural language queries from surgeons. Watson becomes an intelligent surgical assistant.
Second is “machine learning” algorithms. These algorithms use unsupervised pattern matching algorithms that would aid doctors in recognizing when a sequence of symptoms results are matched to a similar pattern of a particular previous surgical issue or result. This will help surgeons have a learning machine at their side.
Third are technologies like “AlphaGo” that trains itself by taking data and training itself to find its own patterns. All the surgical data and outcomes are created and AlphaGo will do the surgeries virtually itself to see if it can first replicate results and then later improve results.
Traditional methods of robotic surgery have not yet embraced AI in specific areas, such as spinal surgery where AI is being leveraged for image recognition through the procedure. Therefore, novel methods are needed to leverage artificial intelligence to improve outcomes for robotic surgery, such as minimally invasive robotic spinal surgery procedures.
The subject matter discussed in the background section should not be assumed to be prior art merely because of its mention in the background section. Similarly, a problem mentioned in the background section or associated with the subject matter of the background section should not be assumed to have been previously recognized in the prior art. The subject matter in the background section merely represents different approaches, which in and of themselves may also correspond to implementations of the claimed technology.